| 1. |
- Indira Chandran, Vineesh, et al.
(författare)
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Ultrasensitive Immunoprofiling of Plasma Extracellular Vesicles Identifies Syndecan-1 as a Potential Tool for Minimally Invasive Diagnosis of Glioma
- 2019
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Ingår i: Clinical Cancer Research. - 1078-0432 .- 1557-3265. ; 25:10, s. 3115-3127
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Tidskriftsartikel (refereegranskat)abstract
- Purpose: Liquid biopsy has great potential to improve the management of brain tumor patients at high risk of surgery-associated complications. Here, the aim was to explore plasma extracellular vesicle (plEV) immunoprofiling as a tool for noninvasive diagnosis of glioma.Experimental Design: PlEV isolation and analysis were optimized using advanced mass spectrometry, nanoparticle tracking analysis, and electron microscopy. We then established a new procedure that combines size exclusion chromatography isolation and proximity extension assay-based ultrasensitive immunoprofiling of plEV proteins that was applied on a well-defined glioma study cohort (n = 82).Results: Among potential candidates, we for the first time identify syndecan-1 (SDC1) as a plEV constituent that can discriminate between high-grade glioblastoma multiforme (GBM, WHO grade IV) and low-grade glioma [LGG, WHO grade II; area under the ROC curve (AUC): 0.81; sensitivity: 71%; specificity: 91%]. These findings were independently validated by ELISA. Tumor SDC1 mRNA expression similarly discriminated between GBM and LGG in an independent glioma patient population from The Cancer Genome Atlas cohort (AUC: 0.91; sensitivity: 79%; specificity: 91%). In experimental studies with GBM cells, we show that SDC1 is efficiently sorted to secreted EVs. Importantly, we found strong support of plEVSDC1 originating from GBM tumors, as plEVSDC1 correlated with SDC1 protein expression in matched patient tumors, and plEVSDC1 was decreased postoperatively depending on the extent of surgery.Conclusions: Our studies support the concept of circulating plEVs as a tool for noninvasive diagnosis and monitoring of gliomas and should move this field closer to the goal of improving the management of cancer patients.
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| 2. |
- Levitsky, Adrian, et al.
(författare)
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Early symptoms and sensations as predictors of lung cancer : a machine learning multivariate model
- 2019
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Ingår i: Scientific Reports. - : Nature Publishing Group. - 2045-2322. ; 9
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Tidskriftsartikel (refereegranskat)abstract
- The aim of this study was to identify a combination of early predictive symptoms/sensations attributable to primary lung cancer (LC). An interactive e-questionnaire comprised of pre-diagnostic descriptors of first symptoms/sensations was administered to patients referred for suspected LC. Respondents were included in the present analysis only if they later received a primary LC diagnosis or had no cancer; and inclusion of each descriptor required >= 4 observations. Fully-completed data from 506/670 individuals later diagnosed with primary LC (n = 311) or no cancer (n = 195) were modelled with orthogonal projections to latent structures (OPLS). After analysing 145/285 descriptors, meeting inclusion criteria, through randomised seven-fold cross-validation (six-fold training set: n = 433; test set: n = 73), 63 provided best LC prediction. The most-significant LC-positive descriptors included a cough that varied over the day, back pain/aches/discomfort, early satiety, appetite loss, and having less strength. Upon combining the descriptors with the background variables current smoking, a cold/flu or pneumonia within the past two years, female sex, older age, a history of COPD (positive LC-association); antibiotics within the past two years, and a history of pneumonia (negative LC-association); the resulting 70-variable model had accurate cross-validated test set performance: area under the ROC curve = 0.767 (descriptors only: 0.736/background predictors only: 0.652), sensitivity = 84.8% (73.9/76.1%, respectively), specificity = 55.6% (66.7/51.9%, respectively). In conclusion, accurate prediction of LC was found through 63 early symptoms/sensations and seven background factors. Further research and precision in this model may lead to a tool for referral and LC diagnostic decision-making.
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| 3. |
- olin, maria, et al.
(författare)
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Patients’ experience of their health changes when under investigation for pulmonary disease – the ongoing PEK-Lung project
- 2015
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Ingår i: European Clinical Respiratory Journal. ; 2:28179
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Konferensbidrag (övrigt vetenskapligt/konstnärligt)abstract
- Introduction: The majority of patients with lung cancer (LC) are diagnosed in advanced stages. Increased specificity about symptoms associated with LC might enable earlier diagnosis. This may allow timely alleviation of symptom distress and increase curative surgical treatment as an option. In this project, we study patients’ subjective experiences of early health changes prior to LC diagnosis and link these changes to biomarker analyses. Method: Patients at initial evaluation at one ambulatory unit at Department of Respiratory Medicine, Karolinska University Hospital, Solna, Sweden, are asked to participate in the project. Patients complete an interactive individualized web-based questionnaire on a touchpad, consisting of 10 subject areas based on 163 descriptors generated through qualitative interviews. An assistant is available for further instructions or assistance. Blood samples are taken for the biobank. Results: From November 3, 2014, to March 1, 2015, 231 new patients were registered at the clinic, of which 195 were invited to participate (12 were excluded due to language difficulties and 24 cancelled their Clinical appointment). In total, 122 (63%) of the patients fulfilling the inclusion criteria were included. Lack of time and fatiguewere commonreasons for non-participation. Our ambition is to include 500 patients. Discussion: This project is a unique collaboration, beginning with patient experiences, including research input spanning from bench to bedside, and driven by a nursing perspective. Challenges for feasibility, especially anchoring, ownership, and communication demands, will be discussed. Keyword: COPD
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| 4. |
- Veerman, Rosanne E., et al.
(författare)
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Molecular evaluation of five different isolation methods for extracellular vesicles reveals different clinical applicability and subcellular origin
- 2021
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Ingår i: Journal of Extracellular Vesicles. - : Wiley. - 2001-3078. ; 10:9
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Tidskriftsartikel (refereegranskat)abstract
- Extracellular vesicles (EVs) are increasingly tested as therapeutic vehicles and biomarkers, but still EV subtypes are not fully characterised. To isolate EVs with few co-isolated entities, a combination of methods is needed. However, this is time-consuming and requires large sample volumes, often not feasible in most clinical studies or in studies where small sample volumes are available. Therefore, we compared EVs rendered by five commonly used methods based on different principles from conditioned cell medium and 250 mu l or 3 ml plasma, that is, precipitation (ExoQuick ULTRA), membrane affinity (exoEasy Maxi Kit), size-exclusion chromatography (qEVoriginal), iodixanol gradient (OptiPrep), and phosphatidylserine affinity (MagCapture). EVs were characterised by electron microscopy, Nanoparticle Tracking Analysis, Bioanalyzer, flow cytometry, and LC-MS/MS. The different methods yielded samples of different morphology, particle size, and proteomic profile. For the conditioned medium, Izon 35 isolated the highest number of EV proteins followed by exoEasy, which also isolated fewer non-EV proteins. For the plasma samples, exoEasy isolated a high number of EV proteins and few non-EV proteins, while Izon 70 isolated the most EV proteins. We conclude that no method is perfect for all studies, rather, different methods are suited depending on sample type and interest in EV subtype, in addition to sample volume and budget.
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| 5. |
- Alexeyenko, Andrey, et al.
(författare)
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Network enrichment analysis : extension of gene-set enrichment analysis to gene networks
- 2012
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Ingår i: BMC Bioinformatics. - : Springer Science and Business Media LLC. - 1471-2105. ; 13, s. 226-
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Tidskriftsartikel (refereegranskat)abstract
- Background: Gene-set enrichment analyses (GEA or GSEA) are commonly used for biological characterization of an experimental gene-set. This is done by finding known functional categories, such as pathways or Gene Ontology terms, that are over-represented in the experimental set; the assessment is based on an overlap statistic. Rich biological information in terms of gene interaction network is now widely available, but this topological information is not used by GEA, so there is a need for methods that exploit this type of information in high-throughput data analysis. Results: We developed a method of network enrichment analysis (NEA) that extends the overlap statistic in GEA to network links between genes in the experimental set and those in the functional categories. For the crucial step in statistical inference, we developed a fast network randomization algorithm in order to obtain the distribution of any network statistic under the null hypothesis of no association between an experimental gene-set and a functional category. We illustrate the NEA method using gene and protein expression data from a lung cancer study. Conclusions: The results indicate that the NEA method is more powerful than the traditional GEA, primarily because the relationships between gene sets were more strongly captured by network connectivity rather than by simple overlaps.
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| 6. |
- Babacic, Haris, et al.
(författare)
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Comprehensive proteomics and meta-analysis of COVID-19 host response
- 2023
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Ingår i: Nature Communications. - : NATURE PORTFOLIO. - 2041-1723. ; 14:1
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Tidskriftsartikel (refereegranskat)abstract
- COVID-19 is characterised by systemic immunological perturbations in the human body, which can lead to multi-organ damage. Many of these processes are considered to be mediated by the blood. Therefore, to better understand the systemic host response to SARS-CoV-2 infection, we performed systematic analyses of the circulating, soluble proteins in the blood through global proteomics by mass-spectrometry (MS) proteomics. Here, we show that a large part of the soluble blood proteome is altered in COVID-19, among them elevated levels of interferon-induced and proteasomal proteins. Some proteins that have alternating levels in human cells after a SARS-CoV-2 infection in vitro and in different organs of COVID-19 patients are deregulated in the blood, suggesting shared infection-related changes.The availability of different public proteomic resources on soluble blood proteome alterations leaves uncertainty about the change of a given protein during COVID-19. Hence, we performed a systematic review and meta-analysis of MS global proteomics studies of soluble blood proteomes, including up to 1706 individuals (1039 COVID-19 patients), to provide concluding estimates for the alteration of 1517 soluble blood proteins in COVID-19. Finally, based on the meta-analysis we developed CoViMAPP, an open-access resource for effect sizes of alterations and diagnostic potential of soluble blood proteins in COVID-19, which is publicly available for the research, clinical, and academic community. Baba & ccaron;ic et al. performed systematic analyses of blood proteins in COVID-19 patients through mass-spectrometry proteomics, showing that a large part of the soluble blood proteome is altered. The authors then developed an open-access resource, CoViMAPP, for meta-analysis of MS proteomics studies of COVID-19 patients.
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| 7. |
- Babacic, Haris, et al.
(författare)
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Glioblastoma stem cells express non-canonical proteins and exclusive mesenchymal-like or non-mesenchymal-like protein signatures
- 2023
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Ingår i: Molecular Oncology. - : John Wiley & Sons. - 1574-7891 .- 1878-0261. ; 17:2, s. 238-260
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Tidskriftsartikel (refereegranskat)abstract
- Glioblastoma (GBM) cancer stem cells (GSCs) contribute to GBM's origin, recurrence, and resistance to treatment. However, the understanding of how mRNA expression patterns of GBM subtypes are reflected at global proteome level in GSCs is limited. To characterize protein expression in GSCs, we performed in-depth proteogenomic analysis of patient-derived GSCs by RNA-sequencing and mass-spectrometry. We quantified > 10 000 proteins in two independent GSC panels and propose a GSC-associated proteomic signature characterizing two distinct phenotypic conditions; one defined by proteins upregulated in proneural and classical GSCs (GPC-like), and another by proteins upregulated in mesenchymal GSCs (GM-like). The GM-like protein set in GBM tissue was associated with necrosis, recurrence, and worse overall survival. Through proteogenomics, we discovered 252 non-canonical peptides in the GSCs, i.e., protein sequences that are variant or derive from genome regions previously considered non-protein-coding, including variants of the heterogeneous ribonucleoproteins implicated in RNA splicing. In summary, GSCs express two protein sets that have an inverse association with clinical outcomes in GBM. The discovery of non-canonical protein sequences questions existing gene models and pinpoints new protein targets for research in GBM.
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| 8. |
- Deutsch, Eric W., et al.
(författare)
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p Advances and Utility of the Human Plasma Proteome
- 2021
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Ingår i: Journal of Proteome Research. - : American Chemical Society (ACS). - 1535-3893 .- 1535-3907. ; 20:12, s. 5241-5263
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Forskningsöversikt (refereegranskat)abstract
- The study of proteins circulating in blood offers tremendous opportunities to diagnose, stratify, or possibly prevent diseases. With recent technological advances and the urgent need to understand the effects of COVID19, the proteomic analysis of blood-derived serum and plasma has become even more important for studying human biology and pathophysiology. Here we provide views and perspectives about technological developments and possible clinical applications that use mass-spectrometry(MS)- or affinity-based methods. We discuss examples where plasma proteomics contributed valuable insights into SARS-CoV-2 infections, aging, and hemostasis and the opportunities offered by combining proteomics with genetic data. As a contribution to the Human Proteome Organization (HUPO) Human Plasma Proteome Project (HPPP), we present the Human Plasma PeptideAtlas build 2021-07 that comprises 4395 canonical and 1482 additional nonredundant human proteins detected in 240 MS-based experiments. In addition, we report the new Human Extracellular Vesicle PeptideAtlas 2021-06, which comprises five studies and 2757 canonical proteins detected in extracellular vesicles circulating in blood, of which 74% (2047) are in common with the plasma PeptideAtlas. Our overview summarizes the recent advances, impactful applications, and ongoing challenges for translating plasma proteomics into utility for precision medicine.
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| 9. |
- Drobin, Kimi
(författare)
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Antibody-based bead arrays for high-throughput protein profiling in human plasma and serum
- 2018
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Licentiatavhandling (övrigt vetenskapligt/konstnärligt)abstract
- Affinity-based proteomics utilizes affinity binders to detect target proteins in a large-scale manner. This thesis describes a high-throughput method, which enables the search for biomarker candidates in human plasma and serum. A highly multiplexed antibody-based suspension bead array is created by coupling antibodies generated in the Human Protein Atlas project to color-coded beads. The beads are combined for parallel analysis of up to 384 analytes in patient and control samples. This provides data to compare protein levels from the different groups.In paper I osteoporosis patients are compared to healthy individuals to find disease-linked proteins. An untargeted discovery screening was conducted using 4608 antibodies in 16 cases and 6 controls. This revealed 72 unique proteins, which appeared differentially abundant. A validation screening of 91 cases and 89 controls confirmed that the protein autocrine motility factor receptor (AMFR) is decreased in the osteoporosis patients.Paper II investigates the risk proteome of inflammatory bowel disease (IBD). Antibodies targeting 209 proteins corresponding to 163 IBD genetic risk loci were selected. To find proteins related to IBD or its subgroups, sera from 49 patients with Crohn’s disease, 51 with ulcerative colitis and 50 matched controls were analyzed. From these targeted assays, the known inflammation-related marker serum amyloid protein A (SAA) was shown to be elevated in the IBD cases. In addition, the protein laccase (multi-copper oxidoreductase) domain containing 1 (LACC1) was found to be decreased in the IBD subjects.In conclusion, assays using affinity-based bead arrays were developed and applied to screen human plasma and serum samples in two disease contexts. Untargeted and targeted screening strategies were applied to discover disease-associated proteins. Upon further validation, these potential biomarker candidates could be valuable in future disease studies.
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| 10. |
- Ezzat, Kariem, et al.
(författare)
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The viral protein corona directs viral pathogenesis and amyloid aggregation
- 2019
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Ingår i: Nature Communications. - : Springer Science and Business Media LLC. - 2041-1723. ; 10
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Tidskriftsartikel (refereegranskat)abstract
- Artificial nanoparticles accumulate a protein corona layer in biological fluids, which significantly influences their bioactivity. As nanosized obligate intracellular parasites, viruses share many biophysical properties with artificial nanoparticles in extracellular environments and here we show that respiratory syncytial virus (RSV) and herpes simplex virus type 1 (HSV-1) accumulate a rich and distinctive protein corona in different biological fluids. Moreover, we show that corona pre-coating differentially affects viral infectivity and immune cell activation. In addition, we demonstrate that viruses bind amyloidogenic peptides in their corona and catalyze amyloid formation via surface-assisted heterogeneous nucleation. Importantly, we show that HSV-1 catalyzes the aggregation of the amyloid beta-peptide (A beta(42)), a major constituent of amyloid plaques in Alzheimer's disease, in vitro and in animal models. Our results highlight the viral protein corona as an acquired structural layer that is critical for viral-host interactions and illustrate a mechanistic convergence between viral and amyloid pathologies.
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